Get Fisher Information From a Design Plan or Simulation Results

Calculates the Fisher information at a planned analysis stage for a design plan or simulation results object for means, rates, survival, or count data endpoints.

Usage

getFisherInformation(designPlan, stage = NA_integer_)

Arguments

designPlan

A trial design plan or simulation results object as returned by functions such as getSampleSizeMeans(), getPowerMeans(), getSampleSizeRates(), getPowerRates(), getSampleSizeSurvival(), getPowerSurvival(), getSampleSizeCounts(), getPowerCounts(), getSimulationMeans(), getSimulationRates(), getSimulationSurvival(), getSimulationCounts(), or the corresponding multi-arm simulation functions.

stage

Integer. The analysis stage for which the Fisher information is requested. If NA (default), the first stage is used.

Value

A numeric value, vector, or matrix containing the requested-stage Fisher information. A vector or matrix can be returned if the object contains several planning alternatives, arms, or sample size values. NA_real_ is returned if the endpoint type is not supported by this helper.

Details

The returned information is the Fisher information used at the requested analysis stage of the design plan or simulation setup. If stage = NA, the first analysis stage is used.

For means, the information is based on the planned sample size, standard deviations, allocation ratio, and, if applicable, the mean-ratio null value. For rates, it is based on the planned sample size and the binomial variance under the corresponding planning assumptions. For survival endpoints, it is based on the planned number of events and the allocation ratio. For count data, it is based on the planned exposure times, event rates, allocation ratio, and overdispersion of the negative binomial model.

See also

getFutilityBounds()

Examples

if (FALSE) { # \dontrun{
designPlan <- getSampleSizeMeans(alternative = 0.4)
getFisherInformation(designPlan)

design <- getDesignGroupSequential(kMax = 3)
designPlan <- getPowerMeans(design,
    alternative = c(0.3, 0.4), maxNumberOfSubjects = 100
)
getFisherInformation(designPlan)

simulationResults <- getSimulationMeans(design,
    plannedSubjects = c(20, 40, 60), alternative = 0.4,
    maxNumberOfIterations = 10
)
getFisherInformation(simulationResults)
} # }